class_docstr: Linear Regression model class
class_docstr_tok: ["Linear","Regression","model","class"]
code: def __call__(self, x):
      # Initialize the model parameters on the first call
      if not self.built:
          # Randomly generate the weight vector and bias term
          rand_w = tf.random.uniform(shape=[x.shape[-1], 1])
          rand_b = tf.random.uniform(shape=[])
          self.w = tf.Variable(rand_w)
          self.b = tf.Variable(rand_b)
          self.built = True
      y = tf.add(tf.matmul(x, self.w), self.b)
      return tf.squeeze(y, axis=1)
  
file_path: mlflow/examples/tensorflow/train.py
imports: import tensorflow
  from sklearn.datasets import fetch_california_housing
  import mlflow
  from mlflow.models import infer_signature
label_desc: Use image node_id 2 for calling the LinearRegression obj's underlying member method code with example usage: obj.__call__(x) and returns: tf